Advancements in number representation for high-precision computing

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Título: Advancements in number representation for high-precision computing
Autor/es: Mora, Higinio | Signes Pont, María Teresa | Pujol, Francisco A. | Mora Pascual, Jerónimo Manuel | García-Chamizo, Juan Manuel
Grupo/s de investigación o GITE: Arquitecturas Inteligentes Aplicadas (AIA) | Informática Industrial y Redes de Computadores | UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Palabras clave: High-performance computing | Architecture and systems | Computer arithmetic | Number representation
Fecha de publicación: 14-dic-2023
Editor: Springer Nature
Cita bibliográfica: The Journal of Supercomputing. 2024, 80: 9742-9761. https://doi.org/10.1007/s11227-023-05814-y
Resumen: Efficient representation of data is a fundamental prerequisite for addressing computational problems effectively using computers. The continual improvement in methods for representing numbers in computers serves as a critical step in expanding the scope and capabilities of computing systems. In this research, we conduct a comprehensive review of both fundamental and advanced techniques for representing numbers in computers. Additionally, we propose a novel model capable of representing rational numbers with absolute precision, catering to specific high precision applications. Specifically, we adopt fractional positional notation coupled with explicit codification of the periodic parts, thereby accommodating the entire rational number set without any loss of accuracy. We elucidate the properties and hardware representation of this proposed format and provide the results of extensive experiments to demonstrate its expressiveness and minimal codification error when compared to other real number representation formats. This research contributes to the advancement of numerical representation in computer systems, empowering them to handle complex computations with heightened accuracy, making them more reliable and versatile in a wide range of applications.
Patrocinador/es: Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the Spanish Research Agency (AEI) (https://doi.org/10.13039/501100011033) under project HPC4Industry PID2020-120213RB-I00.
URI: http://hdl.handle.net/10045/139233
ISSN: 0920-8542 (Print) | 1573-0484 (Online)
DOI: 10.1007/s11227-023-05814-y
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Revisión científica: si
Versión del editor: https://doi.org/10.1007/s11227-023-05814-y
Aparece en las colecciones:INV - AIA - Artículos de Revistas
INV - I2RC - Artículos de Revistas
INV - UNICAD - Artículos de Revistas

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